基于深度学习的无线通信信号调制识别技术研究  

Research on Modulation Recognition Technology of Wireless Communication Signals Based on Deep Learning

作　　者：苗丽萍 MIAO Liping(Jinan Laiwu District Science and Technology Innovation Coordination Service Center,Jinan 271100,China)

机构地区：[1]济南市莱芜区科技创新协调服务中心,山东济南271100

出　　处：《电工技术》2025年第5期79-82,共4页Electric Engineering

摘　　要：信息化时代背景下,将深度学习技术应用到自动调制识别领域已经成为通信行业的重点研究内容之一。针对目前基于深度学习的无线通信信号调制识别技术存在的模型结构复杂和参数庞大等问题,提出一种基于卷积神经网络与门控循环单元技术的调制识别技术,通过该技术可提取同相正交信号的复值特征与单通道特征,并减少系统中的参数量,具有良好的应用效果。In the context of the information age,applying deep learning technology to the field of automatic modulation recognition has become one of the key research topics in the communication industry.In response to the problems of complex model structure and large parameters in current deep learning based wireless communication signal modulation recognition technology,this paper proposes a modulation recognition technology based on convolutional neural network and gated recurrent unit technology.Through this technology,complex features and single channel features of in-phase orthogonal signals can be extracted,and the number of parameters in the system can be reduced,which has good application effects.

关 键 词：深度学习 无线通信 信号调制识别技术 

分 类 号：TN92[电子电信—通信与信息系统]